Analysis of the Bearing Capacity of Shallow Foundation in Unsaturated Soil Using Monte Carlo Simulation

Ravichandran, Nadarajah; Mahmoudabadi, Vahidreza; Shrestha, Shweta

doi:10.4236/ijg.2017.810071

Cited by 18 publications

(4 citation statements)

References 11 publications

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“…It is very useful in estimating the results of physical processes involving stochastic events. It has become a frequently used data generation instrument in geotechnical engineering and in the elimination of uncertainty in soil features [58], in seismic field response analysis [59,60], in overcoming spatial variability in soil deposits, in the analysis of slope stability, in reliability analysis of geotechnical structures [61], and in bearing capacity analysis of shallow foundations [62].…”

Section: Prediction Modelmentioning

confidence: 99%

Use of a Biopolymer for Road Pavement Subgrade

et al. 2023

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This paper presents an extensive series of laboratory works and a prediction model on the design of a road pavement subgrade with Xanthan Gum (XG) biopolymer. The experimental works were carried out using mixtures of conventional aggregate for road pavement construction and XG at the ratios of 0%, 1%, 2%, and 5%, by dry weight. Unconfined compressive strength (UCS) and California bearing ratio (CBR) tests were conducted during the experimental works at the end of the various curing periods (4, 8, 16, and 32 days). An example of an improvement in the UCS values for a specimen with 5% XG addition tested at the end of 4-daycuring yields about a 200% increment by the end of a 32-daycuring. The CBR values of clean aggregates were found to be increased by about 300% by 5% XG addition for all curing periods applied. Furthermore, the energy absorption capacity of the aggregates was observed to be increased significantly by both XG inclusion and curing period. Moreover, scaled conjugate gradient (SCG) training algorithm-based models developed for the prediction of CBR and UCS test results displayed a very high estimation performance with the regression coefficients of R2 = 0.967 and R2 = 0.987, respectively. Evidently, XG biopolymer is provably of use as an alternative inclusion in road pavement subgrades constructed with conventional aggregates.

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Section: Prediction Modelmentioning

confidence: 99%

Use of a Biopolymer for Road Pavement Subgrade

et al. 2023

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“…In SFM, the soil is considered to be uniform, and the influence of spatial variability of soil parameters on bearing capacity is ignored. In order to ensure the safety and stability of the pile foundation, large safety factors are usually given according to engineering experience, which will result in high project costs [4,5]. PFM, based on probability theory, considers the distribution characteristics of each variable and expresses them by partial factors, while traditional methods are still used in the design process [6,7].…”

Section: Introductionmentioning

confidence: 99%

Influence of Correlation Distance of Soil Parameters on Pile Foundation Failure Probability

et al. 2023

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Spatial variability of soil parameter distribution is crucial to calculating the pile foundation failure probability. Traditional reliability design methods describe the dispersion degree of soil parameters with their point variance without considering the influence of correlation distance. In this paper, static cone penetration test data of a project site are used, and random field theory is introduced to describe the average spatial characteristics of soil parameters. Then, the method of spatial average is used to calculate the correlation distance of soil parameters in each foundation soil layer. Given the influence of the correlation distance, a variance reduction function is determined to convert point variance to spatial mean-variance and further calculate the failure probability of pile foundation with the Monte Carlo method to study the influence of correlation distance on pile foundation failure probability. Results show that the spatial variability of parameters can be better reflected, and project cost can be reduced by considering the influence of correlation distance during the pile foundation design process. These results lay a foundation for further research on the pile foundation reliability design method.

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“…So, generally, settlement analysis is required. In the absence of sufficient geotechnical data from site investigation, calculating the bearing pressure required for ultimate shear failure is feasible [3] [4]. Shallow foundations are the easiest and most cost-effective way to support small-to medium-sized structures [5].…”

Section: Introductionmentioning

confidence: 99%

Experimental Study of Bearing Capacity Bridge Foundation Determination

Nagappa¹

2022

ECS Trans.

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Ethiopia is almost mountainous and hilly in topography, with many rivers flowing from the cities' centers. To facilitate transportation, a bridge across the Berbere Wonze River must be built. The bearing capacity of foundation soil is important for foundation design because it can carry heavy loads from the superstructure. The primary goal of this experimental geotechnical investigation is to determine the bearing capacity of foundation soil for the design of bridge foundation at Berbere Wonze River in Amahara Region South Wollo, Kombolcha, Ethiopia. The foundation investigation work includes a Dynamic Cone Penetration (DCP) test, a Standard Penetration Test (SPT), visual identification, groundwater monitoring, soil sampling, and subsequent laboratory tests on representative samples to determine the physical and engineering properties of the subsurface formations and soil underlying the proposed bridge sites. These are to provide safe and cost-effective foundations based on a combination of field data and laboratory test results.

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Analysis of the Bearing Capacity of Shallow Foundation in Unsaturated Soil Using Monte Carlo Simulation

Cited by 18 publications

References 11 publications

Use of a Biopolymer for Road Pavement Subgrade

Use of a Biopolymer for Road Pavement Subgrade

Influence of Correlation Distance of Soil Parameters on Pile Foundation Failure Probability

Experimental Study of Bearing Capacity Bridge Foundation Determination

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